{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# Using Built-in Models\n",
    "\n",
    "[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/brainpy/brainpy/blob/master/docs_version2/tutorial_building/overview_of_dynamic_model.ipynb)\n",
    "[![Open in Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://kaggle.com/kernels/welcome?src=https://github.com/brainpy/brainpy/blob/master/docs_version2/tutorial_building/overview_of_dynamic_model.ipynb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    " @[Tianqiu Zhang](mailto:tianqiuakita@gmail.com) @[Chaoming Wang](mailto:adaduo@outlook.com)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "BrainPy enables modularity programming and easy model debugging. To build a complex brain dynamics model, you just need to group its building blocks. In this section, we are going to talk about what building blocks we provide, and how to use these building blocks.\n"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:45.085704Z",
     "start_time": "2025-10-06T03:57:41.320051Z"
    }
   },
   "source": [
    "import numpy as np\n",
    "\n",
    "import brainpy as bp\n",
    "import brainpy.math as bm\n",
    "\n",
    "bm.set_platform('cpu')"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "cell_type": "code",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:45.098508Z",
     "start_time": "2025-10-06T03:57:45.092517Z"
    }
   },
   "source": [
    "bp.__version__"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'3.0.0'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 2
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initializing a neuron model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "All neuron models implemented in brainpy are subclasses of ``brainpy.dyn.NeuDyn``. The initialization of a neuron model just needs to provide the geometry size of neurons in a population group."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:47.113966Z",
     "start_time": "2025-10-06T03:57:45.110583Z"
    }
   },
   "source": [
    "hh = bp.dyn.HH(size=1)  # only 1 neuron\n",
    "\n",
    "hh = bp.dyn.HH(size=10)  # 10 neurons in a group\n",
    "\n",
    "hh = bp.dyn.HH(size=(10, 10), keep_size=True)  # a grid of (10, 10) neurons in a group\n",
    "\n",
    "hh = bp.dyn.HH(size=(5, 4, 2), keep_size=True)  # a column of (5, 4, 2) neurons in a group"
   ],
   "outputs": [],
   "execution_count": 3
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Generally speaking, there are two types of arguments can be set by users:\n",
    "\n",
    "- **parameters**: the model parameters, like `gNa` refers to the maximum conductance of sodium channel in the ``brainpy.neurons.HH`` model.\n",
    "- **variables**: the model variables, like `V` refers to the membrane potential of a neuron model.\n",
    "\n",
    "In default, model *parameters* are homogeneous, which are just scalar values."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:49.898327Z",
     "start_time": "2025-10-06T03:57:49.475742Z"
    }
   },
   "source": [
    "hh = bp.dyn.HH(5)  # there are five neurons in this group\n",
    "\n",
    "hh.gNa"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "120.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 4
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, neuron models support heterogeneous parameters when performing computations in a neuron group. One can initialize *heterogeneous parameters* by several ways.\n",
    "\n",
    "**1\\. Array**\n",
    "\n",
    "Users can directly provide an array as the parameter."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:50.008271Z",
     "start_time": "2025-10-06T03:57:49.916960Z"
    }
   },
   "source": [
    "hh = bp.dyn.HH(5, gNa=bm.random.uniform(110, 130, size=5))\n",
    "\n",
    "hh.gNa"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Array(value=Array([129.42786 , 128.68614 , 128.45786 , 117.05074 , 118.092705],      dtype=float32), dtype=float32)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 5
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**2\\. Initializer**\n",
    "\n",
    "BrainPy provides wonderful supports on [initializations](../tutorial_toolbox/synaptic_weights.ipynb). One can provide an initializer to the parameter to instruct the model initialize heterogeneous parameters."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:50.053975Z",
     "start_time": "2025-10-06T03:57:50.028040Z"
    }
   },
   "source": [
    "hh = bp.dyn.HH(5, ENa=bp.init.OneInit(50.))\n",
    "\n",
    "hh.ENa"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Array([50., 50., 50., 50., 50.], dtype=float32)"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 6
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**3\\. Callable function**\n",
    "\n",
    "You can also directly provide a callable function which receive a ``shape`` argument."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:50.184453Z",
     "start_time": "2025-10-06T03:57:50.075208Z"
    }
   },
   "source": [
    "hh = bp.dyn.HH(5, ENa=lambda shape: bm.random.uniform(40, 60, shape))\n",
    "\n",
    "hh.ENa"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Array([49.574463, 52.405983, 46.290466, 42.11034 , 48.007538], dtype=float32)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 7
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, let's see how the heterogeneous parameters influence our model simulation."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:50.648694Z",
     "start_time": "2025-10-06T03:57:50.191570Z"
    }
   },
   "source": [
    "# we create 3 neurons in a group. Each neuron has a unique \"gNa\"\n",
    "\n",
    "model = bp.dyn.HH(3, gNa=bp.init.Uniform(min_val=100, max_val=140))"
   ],
   "outputs": [],
   "execution_count": 8
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:50.925019Z",
     "start_time": "2025-10-06T03:57:50.657199Z"
    }
   },
   "source": [
    "inputs = np.ones(int(100./ bm.dt)) * 6.  # 100 ms\n",
    "runner = bp.DSRunner(model, monitors=['V'])\n",
    "runner.run(inputs=inputs)\n",
    "\n",
    "bp.visualize.line_plot(runner.mon.ts, runner.mon.V, plot_ids=[0, 1, 2], show=True)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/1000 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "0a28717da8d845d4858e9ce3968f2b1d"
      }
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'C:\\\\Users\\\\adadu\\\\miniconda3\\\\envs\\\\bdp\\\\Lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 9
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similarly, the setting of the initial values of a variable can also be realized through the above three ways: *Array*, *Initializer*, and *Callable function*. For example,"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:51.018020Z",
     "start_time": "2025-10-06T03:57:50.936765Z"
    }
   },
   "source": [
    "hh = bp.dyn.HH(\n",
    "   3,\n",
    "   V_initializer=bp.init.Uniform(-80., -60.),  # Initializer\n",
    "   m_initializer=lambda shape: bm.random.random(shape),  # function\n",
    "   h_initializer=bm.random.random(3),  # Array\n",
    ")"
   ],
   "outputs": [],
   "execution_count": 10
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:51.030862Z",
     "start_time": "2025-10-06T03:57:51.027463Z"
    }
   },
   "source": [
    "print('V: ', hh.V)\n",
    "print('m: ', hh.m)\n",
    "print('h: ', hh.h)"
   ],
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "V:  Variable(\n",
      "  value=ShapedArray(float32[3]),\n",
      "  _batch_axis=None,\n",
      "  axis_names=None\n",
      ")\n",
      "m:  Variable(\n",
      "  value=ShapedArray(float32[3]),\n",
      "  _batch_axis=None,\n",
      "  axis_names=None\n",
      ")\n",
      "h:  Variable(\n",
      "  value=ShapedArray(float32[3]),\n",
      "  _batch_axis=None,\n",
      "  axis_names=None\n",
      ")\n"
     ]
    }
   ],
   "execution_count": 11
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initializing a synapse model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Initializing a synapse model needs to provide its pre-synaptic group (``pre``), post-synaptic group (``post``) and the connection method between them (``conn``). The below is an example to create an [Exponential synapse model](../apis/auto/dyn/generated/brainpy.dyn.synapses.ExpCUBA.rst):"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:51.065494Z",
     "start_time": "2025-10-06T03:57:51.061594Z"
    }
   },
   "source": [
    "class Exponential(bp.Projection):\n",
    "  def __init__(self, pre, post, prob, weight, delay=None, tau=5., E=0.):\n",
    "    super().__init__()\n",
    "    self.proj = bp.dyn.ProjAlignPostMg2(\n",
    "        pre=pre,\n",
    "        delay=delay, \n",
    "        comm=bp.dnn.CSRLinear(bp.conn.FixedProb(prob, pre=pre.num, post=post.num), weight=weight),\n",
    "        syn=bp.dyn.Expon.desc(size=post.num, tau=tau, sharding=[bm.sharding.NEU_AXIS]),\n",
    "        out=bp.dyn.COBA.desc(E=E),\n",
    "        post=post\n",
    "    )"
   ],
   "outputs": [],
   "execution_count": 12
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:54.431409Z",
     "start_time": "2025-10-06T03:57:51.152802Z"
    }
   },
   "source": [
    "neu = bp.dyn.Lif(10)\n",
    "\n",
    "# here we create a synaptic projection within a population\n",
    "syn = Exponential(neu, neu, 0.02, 0.1)"
   ],
   "outputs": [],
   "execution_count": 13
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "BrainPy's build-in synapse models support **heterogeneous** synaptic weights by using *Array*, *Initializer* and *Callable function*. For example,"
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:55.141379Z",
     "start_time": "2025-10-06T03:57:54.448445Z"
    }
   },
   "source": [
    "syn = Exponential(neu, neu, 0.5, weight=bp.init.Uniform(min_val=0.1, max_val=1.))"
   ],
   "outputs": [],
   "execution_count": 14
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:55.152680Z",
     "start_time": "2025-10-06T03:57:55.147292Z"
    }
   },
   "source": [
    "syn.proj.comm.weight"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Array(value=Array([0.7682079 , 0.49406433, 0.40735582, 0.46180466, 0.6867348 ,\n",
       "                   0.570457  , 0.4389796 , 0.77982205, 0.9423502 , 0.19656381,\n",
       "                   0.8034414 , 0.9204548 , 0.6209335 , 0.55274016, 0.8812761 ,\n",
       "                   0.47911286, 0.2858022 , 0.70651686, 0.36330226, 0.13274   ,\n",
       "                   0.5347911 , 0.42947653, 0.8408286 , 0.8657893 , 0.18790393,\n",
       "                   0.9118224 , 0.72787035, 0.74939704, 0.29419395, 0.3225079 ,\n",
       "                   0.54701155, 0.35412824, 0.80846816, 0.6750682 , 0.74505454,\n",
       "                   0.7918567 , 0.8232436 , 0.7089354 , 0.9901158 , 0.5856384 ,\n",
       "                   0.20930044, 0.38322443, 0.15972926, 0.7810721 , 0.8160317 ,\n",
       "                   0.53544503, 0.1555287 , 0.28004447, 0.9976924 , 0.29718494],      dtype=float32),\n",
       "      dtype=float32)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 15
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, in BrainPy, the built-in synapse models only support homogenous synaptic parameters, like the time constant $\\tau$. Users can [customize their synaptic models](./synapse_models.ipynb) when they want heterogeneous synaptic parameters."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Similar, the synaptic variables can be initialized heterogeneously by using *Array*, *Initializer*, and *Callable functions*."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Changing model parameters during simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In BrainPy, all the dynamically changed variables (no matter it is changed inside or outside the jitted function) should be marked as ``brainpy.math.Variable``. BrainPy's built-in models also support modifying model parameters during simulation."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For example, if you want to fix the `gNa` in the first 100 ms simulation, and then try to decrease its value in the following simulations. In this case, we can provide the `gNa` as an instance of ``brainpy.math.Variable`` when initializing the model."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:55.186317Z",
     "start_time": "2025-10-06T03:57:55.168861Z"
    }
   },
   "source": [
    "hh = bp.dyn.HH(5, gNa=bm.Variable(bm.asarray([120.])))\n",
    "runner = bp.DSRunner(hh, monitors=['V'])"
   ],
   "outputs": [],
   "execution_count": 16
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:55.678237Z",
     "start_time": "2025-10-06T03:57:55.193186Z"
    }
   },
   "source": [
    "# the first running\n",
    "inputs = np.ones(int(100./ bm.dt)) * 6.  # 100 ms\n",
    "runner.run(inputs=inputs)\n",
    "bp.visualize.line_plot(runner.mon.ts, runner.mon.V, show=True)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/1000 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "231769f19b784bc6a29bf48a71e7c1a2"
      }
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'C:\\\\Users\\\\adadu\\\\miniconda3\\\\envs\\\\bdp\\\\Lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 17
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:55.944108Z",
     "start_time": "2025-10-06T03:57:55.697781Z"
    }
   },
   "source": [
    "# change the gNa first\n",
    "hh.gNa[:] = 50.\n",
    "\n",
    "# the second running\n",
    "runner.run(inputs=inputs)\n",
    "bp.visualize.line_plot(runner.mon.ts, runner.mon.V, show=True)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/1000 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "991a462ded224135880d6ee54222632b"
      }
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ],
      "image/png": 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ioox3RkREJA+fA87KlSshCEKX24kTJ+BqrcFYvXo1Zs+ejfT0dBQUFEAQBGzatKldmc8++yxKSkqwdetWnDlzBsuXL/fP07VatWoVzGazZ6uoqPBr+d+lFMU+NUz8eI27xmpEQufz33yXIAiYkhqHj49fhCT1nWchIiLyhs99cFasWIEFCxZ0eUxKSgqqq6sBtO9zo9FokJKSgvLy9ksBxMfHIz4+HqmpqYiOjsaECROwdu1aJCQkXFN2fHw8Ll5sX6vgdDpRV1eH+Pj4Du9Ho9FAo9F483h+0ddWEzfW1EMfqkJchG/vYEpqHN7Yfx4nLzTgpvgIme6OiIjI/3wOOLGxsYiNje32uPT0dGg0GhiNRmRmZgIAHA4HysrKkJSU1Ol5bTU/dru9w/3jxo2DyWTCwYMHkZ6eDgAoKiqCy+VCRkaGr48ji762FtWJGgtuio/wuoNxmx+mDECISsS/jBcZcIiI6LoiWx8cnU6HnJwc5OXlYceOHTAajZ4RU3PmzAEAfPDBBygoKEBpaSnKysqwbds25OTkYPz48UhOTgYAFBcXIzU1FZWVlQCAESNGICsrC4sWLUJxcTE+/fRT5Obm4uc//3mfGEEFAIo+thbViep6pMZ73zzVJkSlwNjkaOw7fVmGuyIiIpKPbMPEASA/Px9KpRLZ2dmw2WzIyMhAUVER9Ho9AECr1eKVV17BsmXLYLfbYTAYcN9992HlypWeMqxWK4xGIxyOb2fVfeutt5Cbm4s777wToihi9uzZeO655+R8FJ+oFAIcfWQeHFtzC8pqG/EfCSk9On/C8Bj8acdJDhcnIqLriiB9D3uQWiwWREZGwmw2Q6fzvWajO0/+3zHsOXUJu5Z3Ptw9UI58Y8K9//0p/rl0PEYZonw+/1iVBT9+bi/e/mUG7hjW/TIPREREcvHl+5trUclApew7NTjGmnoAwI0Dw3t0fmp8BAaEqbGXzVRERHQdYcCRgaoPDRM/d7kRiZEhCFX3rDVSFAWMHxaDTxlwiIjoOsKAIwP3Ug19owanrLYRSQPCelVG5vAYfF1pxpXGZj/dFRERkbwYcGSg7EOdjM9dtiI5ppcBZ1gMJAn47AyXbSAiousDA44MVAqhTzRRSZKE87WNuCGm+xXEu5IYpUVKbBiHixMR0XWDAUcGKoUIRx+YyfhivR3W5hYk97KJCgAmDIvBvtOX/HBXRERE8mPAkYFSIfaJmYzPXW4EANzQyyYqABg/LAYVdTacr23sdVlERERyY8CRgUoU0OKS4ArybMZllxshCIAhundNVADww6EDoBAF7D3FZioiIur7GHBkoFK4X2uwm6nO1TYiMVLrlxmIdSEqjDJEYR8DDhERXQcYcGSgVLgXtQx2R+Oyy41+aZ5qkzksBp+dudyn1tkiIiLqCAOODNStNTjBDjgVdTa/NE+1mTA8BpYmJ76uNPutTCIiIjkw4MhA2RpwmoM8F06lyYbBeq3fyrvNEIVwjRL7TnE0FRER9W0MODLwNFEFsQ9OfZMDZpvDrwFHpRDxw5QB7GhMRER9HgOODPpCE1WlyQYAfg04gLuZqqT8ChrtTr+WS0RE5E8MODJQiu4anGA2UVVecQecQVH+64MDuNelcrRIKD5X59dyiYiI/IkBRwbKPlKDo1IIiIvQ+LXclJgwJEaGsJmKiIj6NAYcGbQ1UQVzwc1vrtiQGKWF2Fqb5C+CIGA8l20gIqI+jgFHBm2djIMZcCqv2DAoyr/9b9pkDo/ByQsNuGBpkqV8IiKi3mLAkUHbTMbOIE6I941JvoAzflgMAHBWYyIi6rMYcGSgaqvBcQa3Bmew3r8djNvEhGuQlqDDvtMMOERE1Dcx4MhA6VmLKjg1OE2OFlxusGOQn4eIX23C8BjsO30ZksRlG4iIqO9hwJFBsGtwaszuvjGJkSGyXWPC8FhcqrfjeHW9bNcgIiLqKQYcGajEtj44wQk41a0BZ6CMAWfsDXqEa5T4+PgF2a5BRETUUww4MlAp24aJB6f5pm10U7xOvoCjUSow8cZY7GLAISKiPogBRwZtMxkHa5h4jaUJESFKhGmUsl5nalocDn9j5nBxIiLqcxhwZKAK8kzGNeYmWWtv2ky+KQ4KUcDHxy/Kfi0iIiJfMODIQCEKEAXAEaQ+OBcsTYiXsf9Nm6hQNcYm69lMRUREfQ4DjkyUCjFoo6iqzU0YGIAaHACYOmIg9p2+DGszVxcnIqK+Q95OGt9jKlEI2kzGFyxNyGydbVhu/5Y2EE9tO449Jy8j65b4gFzTG5IkoazWigPn6nD6UgMqTTY0NbegucWFMLUSUaEqDIrSYmhcOIbHhSMlNhwKP6/bRUREwcOAIxOVUkRzEDoZt7gkXKy3yzpE/GpJA8IwIkGHwiNVfSLgVJls+N8vK7ClpBLldVYIAjBYr4VBH4pQtRK6EBXq7U5UVduw/WgNTFYHACBCo8SoIVEYkxSNscl6jB6ih1atCPLTEBFRTzHgyEQpikHpZFzbYEeLS0JCgJqoAGDmqET8eddJNNidCJd55FZnLliasLHoFN45UAG1QsTdIxOQNyMNP7ghGhEhqg7PkSQJtY3NOFlTj5LyKzh4/gr+tu8snt3lhEoh4NZBkfjBDQOQkRKN9CQ9dJ2UQ0REfY/s30bbtm3Dk08+iSNHjiAkJAQTJ07EP//5TwBAbW0t5s2bhyNHjqC2thZxcXGYOXMmnn76aeh0ug7LKysrw+9+9zsUFRWhpqYGiYmJeOCBB7B69Wqo1Wq5H8draoUAZxBqcGra5sAJUA0OAMy4LRF/+PAEdhytwX23Dw7YdQHA5ZLw1hfn8cftRqgUAlZMuwkP/DDJq6AlCAJiwjWIGabBHa1Nei6XhFMXG1B8rhZfnKvD5pJv8NInZyAKQFqiDj9IHoAf3OAOPDHhaghCYJu1JEmC3emCpckBW3MLHC0uOFqk1v91odkpwelywSUBAgBRECAI7p+Fq34WRQGiIHg6xH/7swCF6D5W0fqZILg7zisEwf15288i2h8juM8X+1FTX2dLkXT0cWf/nOmojM6P7ajcDs734d9OXE2FgkWlEDxLFwWDrAFn8+bNWLRoEZ5++mlMmTIFTqcTpaWlnv2iKGLmzJl46qmnEBsbi9OnT2Pp0qWoq6vD22+/3WGZJ06cgMvlwssvv4xhw4ahtLQUixYtQmNjIzZs2CDn4/hEqRDRHIQanLZlGgLVyRgABkVp8YPkaGz9qiqgAae2wY5H3/kKe09dxv0ZQ/CbrFREantXyyKKAm6Kj8BN8RHIHpcMSZJwvtaK4nN1+PxcLXYcq8H/fHoOAKAPVWH4wAgMjwvHYH0oBuo0GKgLQUy4BqFqBbRqBbQqBRSigBaXBKdLQovLHUbqm5xosDtR3+RAfdPV/+uEpYPP2n62NDmCNoGkL9qCU4cBsJPb9/aLXK4gQUT+tWHObfj39MD+o/dqsgUcp9OJRx55BPn5+Vi4cKHn87S0NM/Per0eS5Ys8fyelJSEhx9+GPn5+Z2Wm5WVhaysLM/vKSkpMBqNePHFF/tYwAlODc4FSxOUooABYYGtzbp3VCLy3j+KS/V2xEZoZL/ewfNXsPStEjhdLry5MAOZw+XpVC0IApJjwpAcE4afjjUAACpNNnz9jQmnLjTg5MUGHDx/BYVHqmG2OXp1rVC1AhEh7n5CESFKRISoEB2mRtKAMOhClNBp2z5XIkKjQqhaAbVShFIhQqUQoFa4f1aK7loUSZIgSe4vcwnun12SO0ZIkoQWl/v3Fpd7X4vnZ/f/uqRv97uk1s3lPs7Vur9F+vb4q8txXXVMRxmn0zqeTmrEOju+47I7KaOTQjr6uPNjfSik07L98Iw+3l+AKxqJAACjDfqgXl+2gFNSUoLKykqIoojRo0ejpqYGo0aNQn5+Pm655ZYOz6mqqsKWLVswceJEn65lNpsRHR3d6X673Q673e753WKx+FR+T6gVYlBmMm4LGIFuJrhnZAKeLDyGzSXfIGfiUFmvtefkJSz++5e4JTESz8+7PaC1VYC7xmpQlBZZ3/lj3ORowUWLHZcammBrdsHmaIHN0QJni8sTPBSiAJVCQJjaHWDaAk2YRhHUqlwiov5GtoBz9uxZAMC6devwzDPPIDk5GX/6058wadIknDx5sl0gmTt3LrZu3QqbzYYZM2bg1Vdf9fo6p0+fxsaNG7usvVm/fj2eeOKJnj9MDygVAhxBGCZ+qSEwNSjfFRWqxj23JuDtL8qxeEKKbAFrx9Ea5L59CJnDY/DCvNsRouo7I51CVAoMGRCKIQNCg30rRETfez7/k3HlypWtnRU739r6yQDA6tWrMXv2bKSnp6OgoACCIGDTpk3tynz22WdRUlKCrVu34syZM1i+fLlX91JZWYmsrCzMmTMHixYt6vS4VatWwWw2e7aKigpfH9tn7lFUQarBCQ98wAGAeT9MQnmdFXtOXZKl/K1fVWLJWyWYmhaHlx5I71PhhoiI+hafa3BWrFiBBQsWdHlMSkoKqqurAbTvc6PRaJCSkoLy8vJ2x8fHxyM+Ph6pqamIjo7GhAkTsHbtWiQkJHR6jaqqKkyePBl33HEH/vrXv3Z5PxqNBhpNYL/03U1UQajBqbcjNb7jEWhyu31IFNISdPjbvnOYdFOcX8t+50A5Vm75Gj8ZPQj/NXskm3OIiKhLPgec2NhYxMbGdntceno6NBoNjEYjMjMzAQAOhwNlZWVISkrq9Ly2mp+r+8x8V2VlJSZPnuypFRLFvvdlp1QIQemDc7mhOShNVIC782TOpKH49T8O4cg3JowcHOWXcv9n3zk8WXgMD/xwCJ6895Z+NQyZiIjkIVsy0Ol0yMnJQV5eHnbs2AGj0egZMTVnzhwAwAcffICCggKUlpairKwM27ZtQ05ODsaPH4/k5GQAQHFxMVJTU1FZWQnAHW4mTZqEIUOGYMOGDbh06RJqampQU1Mj16P0iEoR+In+JEkK2Cimztx9awJuiAnD87tP+6W853efxpOFx7D4Ryn43UyGGyIi8o6s8+Dk5+dDqVQiOzsbNpsNGRkZKCoqgl7vHjqm1WrxyiuvYNmyZbDb7TAYDLjvvvuwcuVKTxlWqxVGoxEOh3sI7s6dO3H69GmcPn0agwe3H1/f2aRcwaAKQg2OxeZEc4srqAFHIQpYOnkY/t+mw/iyrA5jkjsf3dYVSZKQ/5ERL/zrDJZNvRG/vnNYwCfVIyKi65cg9aVUECAWiwWRkZEwm82dzpjcWzl/PwirowVv/OIHspTfkdMX6zH1mT343/8Yhx/c0LNg4Q8ul4RZL3wKlyRh69JMnxexdLkkPFl4DK99VobVPx6BRT9KkelOiYjoeuLL93ff67zST6iUIhzOwNbgXKpvBoCg1uAA7tmA82bcjNJKC/6276xP5zY7XXj0na/w+v4y/P4ntzDcEBFRjzDgyEQlCnC6AhxwGtwds4MdcAAgPUmPxT9KwX9tN+KrCpNX55itDix8/QC2l9bg+ftvx7yMzjujExERdYUBRyaqIAwTv1Rvh1alQJi6b8wP8/+m3YRbBkVi4WsHcPJCfZfHllaaMeO/9+HIN2a89tBY/PjWzqcIICIi6g4DjkyCMUz8Ur0dMRGBX+G6M2qliIIFYxEbocHP//o5ik5cuOaYK43NWP/hccx6/lPotEoU/irTs7I3ERFRT8k6iur7LBjDxC83BG8W487ow9R4e9EPsfx/v8IvXvsStxmikDlsADRKBY5VWfCvkxchScCv7xyO/5iYAo2yb9Q+ERHR9Y0BRyYqhQBHoPvgBHkOnM5Eh6lRsGAsPj5+Ee98WYEtJZVwtLgwNDYcv5oyHD8fa8CAPhbMiIjo+saAIxNlEFYTv1Rvx+1JUQG9prcEQcDUtIGYmjYw2LdCRETfA+yDIxOVKASliSqGNSFEREQMOHJRBbgGp8UlobYxeOtQERER9SUMODJRBniY+BVrM1pcUp/rZExERBQMDDgyUSkEOANYg3Opvu9M8kdERBRsDDgyCfREf7UN7mUa2AeHiIiIAUc2ytZh4oFay7S20V2DEx2mDsj1iIiI+jIGHJmoFCIkyd35NxDqGpuhUYoI7SPLNBAREQUTA45MVAr3cgnOAAacAWF9Z5kGIiKiYGLAkYlSdL/aQA0Vr21shp7NU0RERAAYcGSjUrQFnMDU4FxpbGb/GyIiolYMODLxNFEFsAZnAAMOERERAAYc2XhqcALYByc6jEPEiYiIAAYc2Shba3AczsDU4NQ1NmNAOGtwiIiIAAYc2XzbB0f+gNPiknDF2gx9KAMOERERwIAjm0B2MjbbHJAkTvJHRETUhgFHJuoA1uDUtc5izCYqIiIiNwYcmaiV7j44zQEIOG3rULEGh4iIyI0BRyaeJqoAdDKua3QHHA4TJyIicmPAkYla6X61gajBqbM2QyEK0IWoZL8WERHR9YABRyZtNTjNgajBaWiGPlQFUeQ6VERERAADjmwCOYqqlss0EBERtcOAIxONMpCjqBhwiIiIrsaAI5OANlE1NmMAl2kgIiLyYMCRiUIUoBCFwHQybmyGPowdjImIiNrIHnC2bduGjIwMaLVa6PV6zJo1y7OvtrYWWVlZSExMhEajgcFgQG5uLiwWi1dl2+12jBo1CoIg4KuvvpLnAXpBpRAC2ETFGhwiIqI2sgaczZs3Izs7Gw899BAOHz6MTz/9FPfff/+3FxdFzJw5E++//z5OnjyJ1157Dbt27UJOTo5X5f/nf/4nEhMT5br9XlMpRNmbqCRJam2iYh8cIiKiNkq5CnY6nXjkkUeQn5+PhQsXej5PS0vz/KzX67FkyRLP70lJSXj44YeRn5/fbfkffvghduzYgc2bN+PDDz/07837iUYpyl6D02B3ornFxU7GREREV5GtBqekpASVlZUQRRGjR49GQkICpk+fjtLS0k7PqaqqwpYtWzBx4sQuy75w4QIWLVqEv//97wgNDe32Xux2OywWS7stEFQKEc0yDxPnLMZERETXki3gnD17FgCwbt06rFmzBoWFhdDr9Zg0aRLq6uraHTt37lyEhoZi0KBB0Ol0ePXVVzstV5IkLFiwADk5ORgzZoxX97J+/XpERkZ6NoPB0PMH80EgmqjaAo6eAYeIiMjD54CzcuVKCILQ5XbixAm4XO4v9tWrV2P27NlIT09HQUEBBEHApk2b2pX57LPPoqSkBFu3bsWZM2ewfPnyTq+/ceNG1NfXY9WqVV7f86pVq2A2mz1bRUWFr4/dI+oANFGxBoeIiOhaPvfBWbFiBRYsWNDlMSkpKaiurgbQvs+NRqNBSkoKysvL2x0fHx+P+Ph4pKamIjo6GhMmTMDatWuRkJBwTdlFRUXYv38/NJr2o4bGjBmDefPm4fXXX7/mHI1Gc83xgaBSyB9walmDQ0REdA2fA05sbCxiY2O7PS49PR0ajQZGoxGZmZkAAIfDgbKyMiQlJXV6XlvNj91u73D/c889h6eeesrze1VVFe666y688847yMjI8OVRZKdWCAFpotKFKD0TCxIREZGMo6h0Oh1ycnKQl5cHg8GApKQkz+ioOXPmAAA++OADXLhwAWPHjkV4eDiOHj2Kxx57DOPHj0dycjIAoLi4GPPnz8fHH3+MQYMGYciQIe2uEx4eDgAYOnQoBg8eLNfj9IhaKco+0d8VK5dpICIi+i7ZAg4A5OfnQ6lUIjs7GzabDRkZGSgqKoJerwcAaLVavPLKK1i2bBnsdjsMBgPuu+8+rFy50lOG1WqF0WiEw+GQ81Zl4W6ikncUldnqQGQoAw4REdHVBEmS5F/uuo+xWCyIjIyE2WyGTqeT7ToP/k8xQlQiXs72brRXT+T8/SBsjha8/osfyHYNIiKivsCX72923JCRexSVvPnRZGtGVCjXoSIiIroaA46M1AEYRWWyOhClZcAhIiK6GgOOjFQKAXaZR1GZbeyDQ0RE9F0MODIKxER/rMEhIiK6FgOOjOSe6K/J0QKbo4V9cIiIiL6DAUdGaqW8a1FZbO6h8ww4RERE7THgyEgt8zw4V6zugBOpZR8cIiKiqzHgyEju1cRN1tZ1qFiDQ0RE1A4DjozkXqrB5GmiYg0OERHR1RhwZCR3J2NzaxOVLkTWFTeIiIiuOww4MlIpBDjkbKKyNSMiRAklVxInIiJqh9+MMtLI3URldXAEFRERUQcYcGTUtpq4XOuZmmwORHEEFRER0TUYcGSkam06kmuouJk1OERERB1iwJGRWul+vXI1U5lszYjkMg1ERETXYMCRkacGR6aOxlcaWYNDRETUEQYcGamVAgDINlTczD44REREHWLAkZFaoQAA2GWqwTFZm1mDQ0RE1AEGHBmpFPLV4DQ7XWhsbuEsxkRERB1gwJGRSinfKCpz2zIN7GRMRER0DQYcGalbOxnLseCm2eZeaJNNVERERNdiwJGRnMPETda2hTYZcIiIiL6LAUdG3070J1/AieQoKiIiomsw4MjIU4MjQxOVydYWcFiDQ0RE9F0MODKScxSVydqMMLXCE6KIiIjoW/x2lJGmdR4cuZqoOESciIioYww4MlK1zmQsx0R/XIeKiIiocww4MpJzNXETVxInIiLqFAOOjJSiAEGQp4nKbHNAzyYqIiKiDjHgyEgQBKgUojyjqKwORLIGh4iIqEMMODJTK0R5OhnbmrlMAxERUScYcGSmVoqyzWTMPjhEREQdkzXgbNu2DRkZGdBqtdDr9Zg1a5ZnX21tLbKyspCYmAiNRgODwYDc3FxYLJZeldvXqBSC35uonC0u1Dc5EcVZjImIiDqklKvgzZs3Y9GiRXj66acxZcoUOJ1OlJaWevaLooiZM2fiqaeeQmxsLE6fPo2lS5eirq4Ob7/9do/L7Wvk6INjaXICAPvgEBERdUKWgON0OvHII48gPz8fCxcu9Hyelpbm+Vmv12PJkiWe35OSkvDwww8jPz+/V+X2NRql//vgXLG2riTOPjhEREQdkqWJqqSkBJWVlRBFEaNHj0ZCQgKmT5/eZU1LVVUVtmzZgokTJ/q1XACw2+2wWCzttkDRKBV+n+jv25XE2URFRETUEVkCztmzZwEA69atw5o1a1BYWAi9Xo9Jkyahrq6u3bFz585FaGgoBg0aBJ1Oh1dffdUv5V5t/fr1iIyM9GwGg8EPT+kdtVKE3eHfgGO2tdbgsImKiIioQz4FnJUrV0IQhC63EydOwOVyf6GvXr0as2fPRnp6OgoKCiAIAjZt2tSuzGeffRYlJSXYunUrzpw5g+XLl3d6fV/KvdqqVatgNps9W0VFhS+P3SsapQi7s8WvZbbV4HCpBiIioo751AdnxYoVWLBgQZfHpKSkoLq6GkD7vjEajQYpKSkoLy9vd3x8fDzi4+ORmpqK6OhoTJgwAWvXrkVCQsI1Zbd95k25V9NoNNBoNN0+nxw0KoXfh4mbrA5oVQqEqBR+LZeIiKi/8CngxMbGIjY2ttvj0tPTodFoYDQakZmZCQBwOBwoKytDUlJSp+e11dDY7Xa/lhtMaoX/m6hMNs6BQ0RE1BVZRlHpdDrk5OQgLy8PBoMBSUlJntFRc+bMAQB88MEHuHDhAsaOHYvw8HAcPXoUjz32GMaPH4/k5GQAQHFxMebPn4+PP/7Y00enu3L7Go1KhLm1SclfzFauJE5ERNQV2ebByc/Ph1KpRHZ2Nmw2GzIyMlBUVAS9Xg8A0Gq1eOWVV7Bs2TLY7XYYDAbcd999WLlypacMq9UKo9EIh8Phdbl9jUbp/3lwWINDRETUNUGSJCnYNxFoFosFkZGRMJvN0Ol0sl5r1ZYjOFZlwdbcTL+V+eD/FEOrUuCl7HS/lUlERNTX+fL9zbWoZCbLPDiswSEiIuoSA47M3MPE/T2KqpnLNBAREXWBAUdmajn64FgdXGiTiIioCww4MvP3RH8tLgmWJjZRERERdYUBR2YapcKv8+DUNzkgSVxok4iIqCsMODLTqETY/TiTsWeZBtbgEBERdYoBR2ZqhbsPjr9G45ts7oCj50riREREnWLAkZlG5X7F/hpJZbJyJXEiIqLuMODITKN0L4jpr4Bjbq3B4SgqIiKizjHgyEytcL9ifw0VN1kdUCtFhKj4n46IiKgz/JaU2bdNVP4ZKn7F2oworQqCIPilPCIiov6IAUdm/m6iMlk5Bw4REVF3GHBkplb6t4nKbOMsxkRERN1hwJGZRun/UVScA4eIiKhrDDgy8wQch3/64JhsDs5iTERE1A0GHJmp/VyDY2YfHCIiom4x4MisrZOx34aJ2xyI4izGREREXWLAkZk/ZzJ2uSSYrM2swSEiIuoGA47M2ib688c8OA3NTrgkzmJMRETUHQYcmWn8OEzc1Ni6TANrcIiIiLrEgCMzQRCgVop+aaIy2dwLbUZyFBUREVGXGHACQKMU/dJEZbKyBoeIiMgbDDgBoFGKsDv8UYPTFnDYB4eIiKgrDDgBoFEq0NzS+4BjtjZDKQoIUyv8cFdERET9FwNOAGj81QendZI/riRORETUNQacAFArRb8s1WCyOdjBmIiIyAsMOAGgUYp+aaIyWR3Qs/8NERFRtxhwAkCjVPilk7HZxlmMiYiIvMGAEwB+mwfH6kAkZzEmIiLqFgNOAPhrHpwrXIeKiIjIKww4AaBR+acGx2xzIIqdjImIiLola8DZtm0bMjIyoNVqodfrMWvWLM++2tpaZGVlITExERqNBgaDAbm5ubBYLF2WefLkScycORMxMTHQ6XTIzMzE7t275XyMXlMreh9wJEnyDBMnIiKirskWcDZv3ozs7Gw89NBDOHz4MD799FPcf//9315YFDFz5ky8//77OHnyJF577TXs2rULOTk5XZZ7zz33wOl0oqioCAcPHsRtt92Ge+65BzU1NXI9Sq9plIpeB5zG5hY4XRIiOYqKiIioW0o5CnU6nXjkkUeQn5+PhQsXej5PS0vz/KzX67FkyRLP70lJSXj44YeRn5/fabmXL1/GqVOn8Le//Q0jR44EAPzhD3/ACy+8gNLSUsTHx8vwNL2nUYm9Xk3cZHUvtMkmKiIiou7JUoNTUlKCyspKiKKI0aNHIyEhAdOnT0dpaWmn51RVVWHLli2YOHFip8cMGDAAN910E9544w00NjbC6XTi5ZdfRlxcHNLT0zs9z263w2KxtNsCyR+djLnQJhERkfdkCThnz54FAKxbtw5r1qxBYWEh9Ho9Jk2ahLq6unbHzp07F6GhoRg0aBB0Oh1effXVTssVBAG7du3CoUOHEBERgZCQEDzzzDPYvn079Hp9p+etX78ekZGRns1gMPjnQb2k9sNim+a2hTY5TJyIiKhbPgWclStXQhCELrcTJ07A5XJ/ma9evRqzZ89Geno6CgoKIAgCNm3a1K7MZ599FiUlJdi6dSvOnDmD5cuXd3p9SZKwdOlSxMXFYe/evSguLsasWbMwY8YMVFdXd3reqlWrYDabPVtFRYUvj91rWpXCbzU4kazBISIi6pZPfXBWrFiBBQsWdHlMSkqKJ2xc3edGo9EgJSUF5eXl7Y6Pj49HfHw8UlNTER0djQkTJmDt2rVISEi4puyioiIUFhbiypUr0Ol0AIAXXngBO3fuxOuvv46VK1d2eE8ajQYajcaXR/WrEJUCtuZeBhxbMxSiAF2ILN2miIiI+hWfvi1jY2MRGxvb7XHp6enQaDQwGo3IzMwEADgcDpSVlSEpKanT89pqfux2e4f7rVYrAPcIrKuJoug5ty8KUSlgc7RAkqQerwTunsWYK4kTERF5Q5Y+ODqdDjk5OcjLy8OOHTtgNBo9I6bmzJkDAPjggw9QUFCA0tJSlJWVYdu2bcjJycH48eORnJwMACguLkZqaioqKysBAOPGjYNer8eDDz6Iw4cP4+TJk3jsscdw7tw53H333XI8il9oVQq4JPRqwU2TtZkjqIiIiLwkW3tHfn4+lEolsrOzYbPZkJGRgaKiIk9nYK1Wi1deeQXLli2D3W6HwWDAfffd166ZyWq1wmg0wuFw9z+JiYnB9u3bsXr1akyZMgUOhwM333wztm7dittuu02uR+k1rVoBAGhyuKBRKnpUhsnqYP8bIiIiLwmSJEnBvolAs1gsiIyMhNls9vTlkVPRiQv4xWtf4ovf3omBupAelbHojS/hbHGh4KEf+PnuiIiIrg++fH9zLaoACFG5a21609HYbHUgirMYExEReYUBJwC0rQGnqRdDxU22ZkSyDw4REZFXGHACoK0PTm9qcK5YHdCzBoeIiMgrDDgBENLasdjm6FnAca8k3sxlGoiIiLzEgBMA346i6lnAsTa3wNEiMeAQERF5iQEnANo6GTf1cD2qK20ribOJioiIyCsMOAGg7eUoqrZ1qPSswSEiIvIKA04AqBQCRKHnfXC+DTiswSEiIvIGA04ACIIArUrR4z44bU1UnMmYiIjIOww4AaJV9zzgmGwOKEQBERquJE5EROQNBpwAaVtRvCdMje6FNrmSOBERkXcYcAIkRKWArblno6hMNgeHiBMREfmAASdAtCpFj5dquGJt5hBxIiIiHzDgBIhWpUBTL4aJc4g4ERGR9xhwAiRE3Ys+OKzBISIi8gkDToCEKMVezYMTxZXEiYiIvMaAEyC9HSauD2MNDhERkbcYcAJEq1LA1oO1qFwu90rikazBISIi8hoDToCE9LCTcX2TEy6JyzQQERH5ggEnQHo60Z/J5l6mgaOoiIiIvMeAEyA9XYvqSutCm1yHioiIyHsMOAGiVfdsFJXJ2laDwyYqIiIibzHgBEhPa3BMrTU4XKqBiIjIeww4AaJRKeBokeBs8W0k1RVrM9RKEVqVQqY7IyIi6n8YcAKkLaA0OX0LOG3LNHAlcSIiIu8x4ARIW8Cx+ThU3GRtRpSW/W+IiIh8wYATIFp1aw2Oj/1wTDYH+98QERH5iAEnQEJU7lfta8C5YmXAISIi8hUDToCEtDVR+VqDY23mEHEiIiIfMeAESKhaCQCw+twHx4EoBhwiIiKfMOAESFhrHxxrs9On865Ym9lERURE5CMGnAAJ1bhrcBrt3tfgOFtcqG9ych0qIiIiH8kecLZt24aMjAxotVro9XrMmjWrw+Nqa2sxePBgCIIAk8nUZZl1dXWYN28edDodoqKisHDhQjQ0NPj/5v0otLUPTqPd+xocs611HSoOEyciIvKJrAFn8+bNyM7OxkMPPYTDhw/j008/xf3339/hsQsXLsTIkSO9KnfevHk4evQodu7cicLCQuzZsweLFy/25637nSgKCFUr0OhDH5y6Rvc6VAPCGXCIiIh8oZSrYKfTiUceeQT5+flYuHCh5/O0tLRrjn3xxRdhMpnw+OOP48MPP+yy3OPHj2P79u04cOAAxowZAwDYuHEjfvzjH2PDhg1ITEy85hy73Q673e753WKx9PSxeiVUrYTVhxqc2taAEx3GgENEROQL2WpwSkpKUFlZCVEUMXr0aCQkJGD69OkoLS1td9yxY8fw5JNP4o033oAodn87+/fvR1RUlCfcAMDUqVMhiiK++OKLDs9Zv349IiMjPZvBYOjdw/VQuEaBBh86GXtqcBhwiIiIfCJbwDl79iwAYN26dVizZg0KCwuh1+sxadIk1NXVAXDXrMydOxf5+fkYMmSIV+XW1NQgLi6u3WdKpRLR0dGoqanp8JxVq1bBbDZ7toqKil48Wc+5a3C8b6KqbWyGQhSgC2EnYyIiIl/4HHBWrlwJQRC63E6cOAGXy72o5OrVqzF79mykp6ejoKAAgiBg06ZNANzBY8SIEXjggQf8+1TfodFooNPp2m3BEKZRoNGXGpwG9yR/osiFNomIiHzhcx+cFStWYMGCBV0ek5KSgurqagDt+9xoNBqkpKSgvLwcAFBUVISvv/4a7777LgBAkiQAQExMDFavXo0nnnjimrLj4+Nx8eLFdp85nU7U1dUhPj7e18cJqDCN0qdRVHWNdjZPERER9YDPASc2NhaxsbHdHpeeng6NRgOj0YjMzEwAgMPhQFlZGZKSkgC4R1nZbDbPOQcOHMAvfvEL7N27F0OHDu2w3HHjxsFkMuHgwYNIT08H4A5KLpcLGRkZvj5OQIWplbA0Obw+vraxmR2MiYiIekC2UVQ6nQ45OTnIy8uDwWBAUlIS8vPzAQBz5swBgGtCzOXLlwEAI0aMQFRUFACguLgY8+fPx8cff4xBgwZhxIgRyMrKwqJFi/DSSy/B4XAgNzcXP//5zzscQdWXhKoVqDbbuj+wVR0DDhERUY/IFnAAID8/H0qlEtnZ2bDZbMjIyEBRURH0er3XZVitVhiNRjgc39Z8vPXWW8jNzcWdd94JURQxe/ZsPPfcc3I8gl+5m6h8mwdnaGy4jHdERETUP8kacFQqFTZs2IANGzZ4dfykSZM8/XC6+iw6Ohpvv/223+4zUHzuZMwaHCIioh7hWlQBFKpWer2auCRJuGJt5izGREREPcCAE0DhGiUavBxFZWlywtEisQaHiIioBxhwAihUrUCz0wVHi6vbY+u4TAMREVGPMeAEUJjG3eXJm2aqukb32lkDwjSy3hMREVF/xIATQG0Bx5vJ/mobWINDRETUUww4ARSuUQCAV/1w2pqookK5DhUREZGvGHACqG3RTIut+9mMaxubEalVQaXgfyIiIiJf8dszgCJaA059k3c1OFyHioiIqGcYcAJIp3X3wfFmPSpO8kdERNRzDDgBpFUpoBAFWLyswWHAISIi6hkGnAASBAG6ECXqvazB4SzGREREPcOAE2A6rQoWG2twiIiI5MSAE2ARXtTgSJKES/V2xIZzkj8iIqKeYMAJMF2Iqts+OCarA80tLsTpQgJ0V0RERP0LA06AeVODc6nBvUxDXARrcIiIiHqCASfAdCGqbif6u2hxB5xYBhwiIqIeYcAJsIgQVbcT/V2sbwIAxEWwiYqIiKgnGHACTKdVdjvR36V6OyI0SmjVigDdFRERUf/CgBNg3tXg2Nk8RURE1AsMOAGmC1HC2twCR4ur02MYcIiIiHqHASfAokLdk/eZu+hofKm+iUPEiYiIeoEBJ8Ciw9wril9pbO70mIv1dg4RJyIi6gUGnADTt9bg1HYRcC5Z2ERFRETUGww4ATYgzB1cOqvBsTW3oN7uZA0OERFRLzDgBFhEiBIKUUCdteOAc6m+bRZj9sEhIiLqKQacABNFAfpQFeoaOg44bZP8sYmKiIio5xhwgkAfqu60BqfK7A44iVGswSEiIuopBpwg0IepO+2DU2WyISJEiYgQVYDvioiIqP9gwAmCAWFq1Fk7ngenymRDYqQ2wHdERETUvzDgBIE+TI26RnuH+6pMNjZPERER9RIDThBEh6pxpbHjGpxKUxMSo1iDQ0RE1BuyB5xt27YhIyMDWq0Wer0es2bN6vC42tpaDB48GIIgwGQydVpeWVkZFi5ciBtuuAFarRZDhw5FXl4emps7nzivrxkQrsalBjskSbpmX7XZxoBDRETUS0o5C9+8eTMWLVqEp59+GlOmTIHT6URpaWmHxy5cuBAjR45EZWVll2WeOHECLpcLL7/8MoYNG4bS0lIsWrQIjY2N2LBhgxyP4XcJkSFodrpwxepAdJja83mj3QmT1YFBDDhERES9IlvAcTqdeOSRR5Cfn4+FCxd6Pk9LS7vm2BdffBEmkwmPP/44Pvzwwy7LzcrKQlZWluf3lJQUGI1GvPjii9dNwIlv7URcZbK1CzjfXLEBAGtwiIiIekm2JqqSkhJUVlZCFEWMHj0aCQkJmD59+jU1OMeOHcOTTz6JN954A6LYs9sxm82Ijo7udL/dbofFYmm3BVNipLsTcU3rnDdtzl1uBAAkx4QG/J6IiIj6E9kCztmzZwEA69atw5o1a1BYWAi9Xo9Jkyahrq4OgDt4zJ07F/n5+RgyZEiPrnP69Gls3LgR//Ef/9HpMevXr0dkZKRnMxgMPbqWv8SEa6AUBVSbbe0+L6ttRJhagdhwzmJMRETUGz4HnJUrV0IQhC63tn4yALB69WrMnj0b6enpKCgogCAI2LRpEwBg1apVGDFiBB544IEe3XxlZSWysrIwZ84cLFq0qNPjVq1aBbPZ7NkqKip6dD1/EUUBA3UhqP5ODU7Z5UYkx4RBEIQg3RkREVH/4HMfnBUrVmDBggVdHpOSkoLq6moA7fvcaDQapKSkoLy8HABQVFSEr7/+Gu+++y4AeEYVxcTEYPXq1XjiiSc6vUZVVRUmT56MO+64A3/961+7vB+NRgONpm/ViiRGhXTYRJUcExakOyIiIuo/fA44sbGxiI2N7fa49PR0aDQaGI1GZGZmAgAcDgfKysqQlJQEwD3Kymb7tpnmwIED+MUvfoG9e/di6NChnZZdWVmJyZMne2qFetp3J5jiI7Wo6qCJamxy532JiIiIyDuyjaLS6XTIyclBXl4eDAYDkpKSkJ+fDwCYM2cOAFwTYi5fvgwAGDFiBKKiogAAxcXFmD9/Pj7++GMMGjQIlZWVmDRpEpKSkrBhwwZcunTJc358fLxcj+N3iVEhOFR+xfN7g92JCxY7bmANDhERUa/JOg9Ofn4+lEolsrOzYbPZkJGRgaKiIuj1eq/LsFqtMBqNcDjcM//u3LkTp0+fxunTpzF48OB2x3Y0cV5fNTQmHJUmG5ocLQhRKXC00gwASEvUBfnOiIiIrn+CdD2lAj+xWCyIjIyE2WyGThecQHHwfB1mv7gfHz4yASMSdHh171nkf2TE0SfuglJx/TW5ERERyc2X729+kwbJsNgIAICxph4A8HWlGWmJOoYbIiIiP+C3aZBEhqqQNCAUh78xAXAHnJGDIoN7U0RERP0EA04QjTJE4UBZHapMNpy91Ih0jqAiIiLyCwacIJp8UxxKKy34656zUIoCJt7Y/fB7IiIi6h4DThDdOSIO+lAVXvusDLNGD0KkVhXsWyIiIuoXZB0mTl2LCFHhbwvGYsfRC3h4cucTGxIREZFvGHCC7PYhetw+xPt5gYiIiKh7bKIiIiKifocBh4iIiPodBhwiIiLqdxhwiIiIqN9hwCEiIqJ+hwGHiIiI+h0GHCIiIup3GHCIiIio32HAISIion6HAYeIiIj6HQYcIiIi6ncYcIiIiKjfYcAhIiKifocBh4iIiPodZbBvIBgkSQIAWCyWIN8JEREReavte7vte7wr38uAU19fDwAwGAxBvhMiIiLyVX19PSIjI7s8RpC8iUH9jMvlQlVVFSIiIiAIgl/LtlgsMBgMqKiogE6n82vZ9C2+58Dgew4cvuvA4HsODLnesyRJqK+vR2JiIkSx614238saHFEUMXjwYFmvodPp+H+eAOB7Dgy+58Dhuw4MvufAkOM9d1dz04adjImIiKjfYcAhIiKifocBx880Gg3y8vKg0WiCfSv9Gt9zYPA9Bw7fdWDwPQdGX3jP38tOxkRERNS/sQaHiIiI+h0GHCIiIup3GHCIiIio32HAISIion6HAccLe/bswYwZM5CYmAhBEPDPf/6z3X5JkvD4448jISEBWq0WU6dOxalTp9odU1dXh3nz5kGn0yEqKgoLFy5EQ0NDAJ+i7+vqPTscDvzmN7/BrbfeirCwMCQmJmL+/PmoqqpqVwbfs3e6+zN9tZycHAiCgD//+c/tPue77p437/n48eO49957ERkZibCwMIwdOxbl5eWe/U1NTVi6dCkGDBiA8PBwzJ49GxcuXAjgU/R93b3nhoYG5ObmYvDgwdBqtUhLS8NLL73U7hi+5+6tX78eY8eORUREBOLi4jBr1iwYjcZ2x3jzHsvLy3H33XcjNDQUcXFxeOyxx+B0Ov1+vww4XmhsbMRtt92G559/vsP9//Vf/4XnnnsOL730Er744guEhYXhrrvuQlNTk+eYefPm4ejRo9i5cycKCwuxZ88eLF68OFCPcF3o6j1brVaUlJRg7dq1KCkpwZYtW2A0GnHvvfe2O47v2Tvd/Zlu89577+Hzzz9HYmLiNfv4rrvX3Xs+c+YMMjMzkZqain/96184cuQI1q5di5CQEM8xy5Ytw//93/9h06ZN+OSTT1BVVYX77rsvUI9wXejuPS9fvhzbt2/Hm2++iePHj+PRRx9Fbm4u3n//fc8xfM/d++STT7B06VJ8/vnn2LlzJxwOB6ZNm4bGxkbPMd29x5aWFtx9991obm7GZ599htdffx2vvfYaHn/8cf/fsEQ+ASC99957nt9dLpcUHx8v5efnez4zmUySRqOR/vGPf0iSJEnHjh2TAEgHDhzwHPPhhx9KgiBIlZWVAbv368l333NHiouLJQDS+fPnJUnie+6pzt71N998Iw0aNEgqLS2VkpKSpGeffdazj+/adx2955/97GfSAw880Ok5JpNJUqlU0qZNmzyfHT9+XAIg7d+/X65bva519J5vvvlm6cknn2z32e233y6tXr1akiS+5566ePGiBED65JNPJEny7j1+8MEHkiiKUk1NjeeYF198UdLpdJLdbvfr/bEGp5fOnTuHmpoaTJ061fNZZGQkMjIysH//fgDA/v37ERUVhTFjxniOmTp1KkRRxBdffBHwe+4vzGYzBEFAVFQUAL5nf3K5XMjOzsZjjz2Gm2+++Zr9fNe953K5sG3bNtx444246667EBcXh4yMjHbNKwcPHoTD4Wj390tqaiqGDBni+fuFunfHHXfg/fffR2VlJSRJwu7du3Hy5ElMmzYNAN9zT5nNZgBAdHQ0AO/e4/79+3Hrrbdi4MCBnmPuuusuWCwWHD161K/3x4DTSzU1NQDQ7j9W2+9t+2pqahAXF9duv1KpRHR0tOcY8k1TUxN+85vfYO7cuZ6F3Pie/eePf/wjlEolfv3rX3e4n++69y5evIiGhgb84Q9/QFZWFnbs2IGf/OQnuO+++/DJJ58AcL9ntVrtCfFtrv77hbq3ceNGpKWlYfDgwVCr1cjKysLzzz+PH/3oRwD4nnvC5XLh0Ucfxfjx43HLLbcA8O491tTUdPh92bbPn76Xq4nT9c3hcOCnP/0pJEnCiy++GOzb6XcOHjyIv/zlLygpKYEgCMG+nX7L5XIBAGbOnIlly5YBAEaNGoXPPvsML730EiZOnBjM2+tXNm7ciM8//xzvv/8+kpKSsGfPHixduhSJiYntahvIe0uXLkVpaSn27dsX7FvpFGtweik+Ph4AruklfuHCBc+++Ph4XLx4sd1+p9OJuro6zzHknbZwc/78eezcudNTewPwPfvL3r17cfHiRQwZMgRKpRJKpRLnz5/HihUrkJycDIDv2h9iYmKgVCqRlpbW7vMRI0Z4RlHFx8ejubkZJpOp3TFX//1CXbPZbPjtb3+LZ555BjNmzMDIkSORm5uLn/3sZ9iwYQMAvmdf5ebmorCwELt378bgwYM9n3vzHuPj4zv8vmzb508MOL10ww03ID4+Hh9//LHnM4vFgi+++ALjxo0DAIwbNw4mkwkHDx70HFNUVASXy4WMjIyA3/P1qi3cnDp1Crt27cKAAQPa7ed79o/s7GwcOXIEX331lWdLTEzEY489ho8++ggA37U/qNVqjB079pphtidPnkRSUhIAID09HSqVqt3fL0ajEeXl5Z6/X6hrDocDDocDotj+606hUHhq0fievSNJEnJzc/Hee++hqKgIN9xwQ7v93rzHcePG4euvv273D6S2f6x+N+z744apG/X19dKhQ4ekQ4cOSQCkZ555Rjp06JBn9M4f/vAHKSoqStq6dat05MgRaebMmdINN9wg2Ww2TxlZWVnS6NGjpS+++ELat2+fNHz4cGnu3LnBeqQ+qav33NzcLN17773S4MGDpa+++kqqrq72bFf3vOd79k53f6a/67ujqCSJ79ob3b3nLVu2SCqVSvrrX/8qnTp1Stq4caOkUCikvXv3esrIycmRhgwZIhUVFUlffvmlNG7cOGncuHHBeqQ+qbv3PHHiROnmm2+Wdu/eLZ09e1YqKCiQQkJCpBdeeMFTBt9z95YsWSJFRkZK//rXv9r9HWy1Wj3HdPcenU6ndMstt0jTpk2TvvrqK2n79u1SbGystGrVKr/fLwOOF3bv3i0BuGZ78MEHJUlyDxVfu3atNHDgQEmj0Uh33nmnZDQa25VRW1srzZ07VwoPD5d0Op300EMPSfX19UF4mr6rq/d87ty5DvcBkHbv3u0pg+/ZO939mf6ujgIO33X3vHnPf/vb36Rhw4ZJISEh0m233Sb985//bFeGzWaTHn74YUmv10uhoaHST37yE6m6ujrAT9K3dfeeq6urpQULFkiJiYlSSEiIdNNNN0l/+tOfJJfL5SmD77l7nf0dXFBQ4DnGm/dYVlYmTZ8+XdJqtVJMTIy0YsUKyeFw+P1+hdabJiIiIuo32AeHiIiI+h0GHCIiIup3GHCIiIio32HAISIion6HAYeIiIj6HQYcIiIi6ncYcIiIiKjfYcAhIiKifocBh4gCZsGCBZg1a1bQrp+dnY2nn35atvKPHTuGwYMHo7GxUbZrEJF3OJMxEfmFIAhd7s/Ly8OyZcsgSRKioqICc1NXOXz4MKZMmYLz588jPDxctuv8+7//O2677TasXbtWtmsQUfcYcIjIL2pqajw/v/POO3j88cfbrZQdHh4ua7Dozi9/+UsolUq89NJLsl5n27ZtWLRoEcrLy6FUKmW9FhF1jk1UROQX8fHxni0yMhKCILT7LDw8/JomqkmTJuFXv/oVHn30Uej1egwcOBCvvPIKGhsb8dBDDyEiIgLDhg3Dhx9+2O5apaWlmD59OsLDwzFw4EBkZ2fj8uXLnd5bS0sL3n33XcyYMaPd58nJyXjqqacwf/58hIeHIykpCe+//z4uXbqEmTNnIjw8HCNHjsSXX37pOef8+fOYMWMG9Ho9wsLCcPPNN+ODDz7w7P+3f/s31NXV4ZNPPunlGyWi3mDAIaKgev311xETE4Pi4mL86le/wpIlSzBnzhzccccdKCkpwbRp05CdnQ2r1QoAMJlMmDJlCkaPHo0vv/wS27dvx4ULF/DTn/6002scOXIEZrMZY8aMuWbfs88+i/Hjx+PQoUO4++67kZ2djfnz5+OBBx5ASUkJhg4divnz56Otsnvp0qWw2+3Ys2cPvv76a/zxj39sVzOlVqsxatQo7N27189vioh84vf1yYnoe6+goECKjIy85vMHH3xQmjlzpuf3iRMnSpmZmZ7fnU6nFBYWJmVnZ3s+q66ulgBI+/fvlyRJkn73u99J06ZNa1duRUWFBEAyGo0d3s97770nKRQKyeVytfs8KSlJeuCBB6651tq1az2f7d+/XwIgVVdXS5IkSbfeequ0bt26Lp//Jz/5ibRgwYIujyEiebEGh4iCauTIkZ6fFQoFBgwYgFtvvdXz2cCBAwEAFy9eBODuLLx7925Pn57w8HCkpqYCAM6cOdPhNWw2GzQaTYcdoa++ftu1urr+r3/9azz11FMYP3488vLycOTIkWvK1Gq1nhonIgoOBhwiCiqVStXud0EQ2n3WFkpcLhcAoKGhATNmzMBXX33Vbjt16hR+9KMfdXiNmJgYWK1WNDc3d3n9tmt1df1f/vKXOHv2LLKzs/H1119jzJgx2LhxY7sy6+rqEBsb690LICJZMOAQ0XXl9ttvx9GjR5GcnIxhw4a128LCwjo8Z9SoUQDc89T4g8FgQE5ODrZs2YIVK1bglVdeabe/tLQUo0eP9su1iKhnGHCI6LqydOlS1NXVYe7cuThw4ADOnDmDjz76CA899BBaWlo6PCc2Nha333479u3b1+vrP/roo/joo49w7tw5lJSUYPfu3RgxYoRnf1lZGSorKzF16tReX4uIeo4Bh4iuK4mJifj000/R0tKCadOm4dZbb8Wjjz6KqKgoiGLnf6X98pe/xFtvvdXr67e0tGDp0qUYMWIEsrKycOONN+KFF17w7P/HP/6BadOmISkpqdfXIqKe40R/RPS9YLPZcNNNN+Gdd97BuHHjZLlGc3Mzhg8fjrfffhvjx4+X5RpE5B3W4BDR94JWq8Ubb7zR5YSAvVVeXo7f/va3DDdEfQBrcIiIiKjfYQ0OERER9TsMOERERNTvMOAQERFRv8OAQ0RERP0OAw4RERH1Oww4RERE1O8w4BAREVG/w4BDRERE/Q4DDhEREfU7/x/KEjIowBG/UwAAAABJRU5ErkJggg=="
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'C:\\\\Users\\\\adadu\\\\miniconda3\\\\envs\\\\bdp\\\\Lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 18
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Examples of using built-in models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here we show users how to simulate a famous neuron models: [The Morris-Lecar neuron model](../apis/auto/dyn/generated/brainpy.dyn.neurons.MorrisLecar.rst), which is a two-dimensional \"reduced\" excitation model applicable to systems having two non-inactivating voltage-sensitive conductances."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:56.046053Z",
     "start_time": "2025-10-06T03:57:55.961226Z"
    }
   },
   "source": [
    "group = bp.dyn.MorrisLecar(1)"
   ],
   "outputs": [],
   "execution_count": 19
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then users can utilize various tools provided by BrainPy to easily simulate the Morris-Lecar neuron model. Here we are not going to dive into details so please read the corresponding tutorials if you want to learn more."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:56.327069Z",
     "start_time": "2025-10-06T03:57:56.053537Z"
    }
   },
   "source": [
    "runner = bp.DSRunner(group, monitors=['V', 'W'])\n",
    "\n",
    "inputs = np.ones(int(100./ bm.dt)) * 100.  # 100 ms\n",
    "runner.run(inputs=inputs)\n",
    "\n",
    "fig, gs = bp.visualize.get_figure(2, 1, 3, 8)\n",
    "fig.add_subplot(gs[0, 0])\n",
    "bp.visualize.line_plot(runner.mon.ts, runner.mon.W, ylabel='W')\n",
    "fig.add_subplot(gs[1, 0])\n",
    "bp.visualize.line_plot(runner.mon.ts, runner.mon.V, ylabel='V', show=True)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/1000 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "70ff18f06750478a9ec30f14270c21af"
      }
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<module 'matplotlib.pyplot' from 'C:\\\\Users\\\\adadu\\\\miniconda3\\\\envs\\\\bdp\\\\Lib\\\\site-packages\\\\matplotlib\\\\pyplot.py'>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 20
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we will also give users an intuitive understanding about building a network composed of different neurons and synapses model. Users can simply initialize these models as below and pass into ``brainpy.DynSysGroup``."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:56.340834Z",
     "start_time": "2025-10-06T03:57:56.336553Z"
    }
   },
   "source": [
    "class AMPA(bp.Projection):\n",
    "    def __init__(self, pre, post, delay, g_max, E=0.):\n",
    "        super().__init__()\n",
    "        self.proj = bp.dyn.ProjAlignPreMg2(\n",
    "          pre=pre, \n",
    "          delay=delay, \n",
    "          syn=bp.dyn.AMPA.desc(pre.num, alpha=0.98, beta=0.18, T=0.5, T_dur=0.5),\n",
    "          comm=bp.dnn.AllToAll(pre.num, post.num, g_max),\n",
    "          out=bp.dyn.COBA(E=E),\n",
    "          post=post, \n",
    "        )"
   ],
   "outputs": [],
   "execution_count": 21
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:56.365986Z",
     "start_time": "2025-10-06T03:57:56.355871Z"
    }
   },
   "source": [
    "neu1 = bp.neurons.HH(1)\n",
    "neu2 = bp.neurons.HH(1)\n",
    "syn1 = AMPA(neu1, neu2, None, 1.)\n",
    "net = bp.DynSysGroup(pre=neu1, syn=syn1, post=neu2)"
   ],
   "outputs": [],
   "execution_count": 22
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By selecting proper runner, users can simulate the network efficiently and plot the simulation results."
   ]
  },
  {
   "cell_type": "code",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-06T03:57:56.767230Z",
     "start_time": "2025-10-06T03:57:56.372749Z"
    }
   },
   "source": [
    "runner = bp.DSRunner(net,\n",
    "                     inputs=(neu1.input, 6.),\n",
    "                     monitors={'pre.V': neu1.V, 'post.V': neu2.V, 'syn.g': syn1.proj.refs['syn'].g})\n",
    "runner.run(150.)\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, gs = bp.visualize.get_figure(2, 1, 3, 8)\n",
    "fig.add_subplot(gs[0, 0])\n",
    "plt.plot(runner.mon.ts, runner.mon['pre.V'], label='pre-V')\n",
    "plt.plot(runner.mon.ts, runner.mon['post.V'], label='post-V')\n",
    "plt.legend()\n",
    "\n",
    "fig.add_subplot(gs[1, 0])\n",
    "plt.plot(runner.mon.ts, runner.mon['syn.g'], label='g')\n",
    "plt.legend()\n",
    "plt.show()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "  0%|          | 0/1500 [00:00<?, ?it/s]"
      ],
      "application/vnd.jupyter.widget-view+json": {
       "version_major": 2,
       "version_minor": 0,
       "model_id": "1b55cea287bb4cc79ac38865da1d3f10"
      }
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 800x600 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 23
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
